A convex approach to steady state moment analysis for stochastic chemical reactions

Yuta Sakurai, Yutaka Hori

研究成果: Conference contribution

5 引用 (Scopus)

抜粋

Model-based prediction of stochastic noise in biomolecular reactions often resorts to approximation with unknown precision. As a result, unexpected stochastic fluctuation causes a headache for the designers of biomolecular circuits. This paper proposes a convex optimization approach to quantifying the steady state moments of molecular copy counts with theoretical rigor. We show that the stochastic moments lie in a convex semi-algebraic set specified by linear matrix inequalities. Thus, the upper and the lower bounds of some moments can be computed by a semidefinite program. Using a protein dimerization process as an example, we demonstrate that the proposed method can precisely predict the mean and the variance of the copy number of the monomer protein.

元の言語English
ホスト出版物のタイトル2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
出版者Institute of Electrical and Electronics Engineers Inc.
ページ1206-1211
ページ数6
2018-January
ISBN(電子版)9781509028733
DOI
出版物ステータスPublished - 2018 1 18
イベント56th IEEE Annual Conference on Decision and Control, CDC 2017 - Melbourne, Australia
継続期間: 2017 12 122017 12 15

Other

Other56th IEEE Annual Conference on Decision and Control, CDC 2017
Australia
Melbourne
期間17/12/1217/12/15

ASJC Scopus subject areas

  • Decision Sciences (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Control and Optimization

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  • これを引用

    Sakurai, Y., & Hori, Y. (2018). A convex approach to steady state moment analysis for stochastic chemical reactions. : 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017 (巻 2018-January, pp. 1206-1211). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2017.8263820